MCP 服务工具

by JQSC

AI/Development Tools Hugging Face Dify API

This is a collection of MCP (Model Context Protocol) service tools for calling various AI service APIs. It supports Hugging Face and Dify services.

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What is MCP 服务工具?

MCP 服务工具 is a collection of tools designed to facilitate the integration and utilization of various AI services through the Model Context Protocol (MCP). It provides a unified interface for interacting with services like Hugging Face and Dify, simplifying the process of calling AI APIs.

How to use MCP 服务工具?

To use the MCP 服务工具, first install the necessary dependencies using npm install. Then, configure the API keys and base URLs for Hugging Face and Dify in a .env file. Finally, you can use the provided functions and classes to call the desired AI services, as demonstrated in the usage examples.

Key features of MCP 服务工具

Supports Hugging Face NLP, CV, and speech processing tasks
Supports Dify conversational and text generation applications
Provides tools for managing Dify conversation history and lists
Offers a unified interface for interacting with different AI services

Use cases of MCP 服务工具

Building AI-powered chatbots using Dify
Integrating NLP tasks like text generation and classification into applications
Performing image analysis tasks like image classification and segmentation
Automating speech recognition processes

FAQ from MCP 服务工具

What is MCP?

MCP stands for Model Context Protocol. It's a protocol for interacting with AI models and services.

Do I need API keys to use this tool?

Yes, you need API keys for the AI services you want to use (e.g., Hugging Face, Dify).

How do I install the dependencies?

Run npm install in the project directory.

How do I configure the API keys?

Create a .env file in the project root and add the API keys as environment variables.

Are there any API usage limits?

Yes, please check the API documentation for Hugging Face and Dify for their respective usage limits and fees.